




from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class 				lowerCAmelCase_       (					lowerCamelCase_							):
				__a     :       Tuple						=     ["image_processor", "tokenizer"]
				__a     :       Optional[int]						=     "BlipImageProcessor"
				__a     :       Union[str, Any]						=     "AutoTokenizer"






				def __init__(			self      ,snake_case__      ,snake_case__ ):
							SCREAMING_SNAKE_CASE_   : Tuple					  =      False
							super().__init__(snake_case__      ,snake_case__ )
							SCREAMING_SNAKE_CASE_   : str					  =      self.image_processor






				def __call__(			self      ,snake_case__ = None      ,snake_case__ = None      ,snake_case__ = True      ,snake_case__ = False      ,snake_case__ = None      ,snake_case__ = None      ,snake_case__ = 0      ,snake_case__ = None      ,snake_case__ = None      ,snake_case__ = False      ,snake_case__ = False      ,snake_case__ = False      ,snake_case__ = False      ,snake_case__ = False      ,snake_case__ = True      ,snake_case__ = None      ,**snake_case__      ,):
							if images is None and text is None:
										raise ValueError('You have to specify either images or text.' )

							# Get only text
							if images is None:
										SCREAMING_SNAKE_CASE_   : List[str]					  =      self.tokenizer
										SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      self.tokenizer(
										    text=snake_case__      ,add_special_tokens=snake_case__      ,padding=snake_case__      ,truncation=snake_case__      ,max_length=snake_case__      ,stride=snake_case__      ,pad_to_multiple_of=snake_case__      ,return_attention_mask=snake_case__      ,return_overflowing_tokens=snake_case__      ,return_special_tokens_mask=snake_case__      ,return_offsets_mapping=snake_case__      ,return_token_type_ids=snake_case__      ,return_length=snake_case__      ,verbose=snake_case__      ,return_tensors=snake_case__      ,**snake_case__      ,)
										return text_encoding

							# add pixel_values
							SCREAMING_SNAKE_CASE_   : Dict					  =      self.image_processor(snake_case__      ,return_tensors=snake_case__ )

							if text is not None:
										SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      self.tokenizer(
										    text=snake_case__      ,add_special_tokens=snake_case__      ,padding=snake_case__      ,truncation=snake_case__      ,max_length=snake_case__      ,stride=snake_case__      ,pad_to_multiple_of=snake_case__      ,return_attention_mask=snake_case__      ,return_overflowing_tokens=snake_case__      ,return_special_tokens_mask=snake_case__      ,return_offsets_mapping=snake_case__      ,return_token_type_ids=snake_case__      ,return_length=snake_case__      ,verbose=snake_case__      ,return_tensors=snake_case__      ,**snake_case__      ,)
							else:
										SCREAMING_SNAKE_CASE_   : Tuple					  =      None

							if text_encoding is not None:
										encoding_image_processor.update(snake_case__ )

							return encoding_image_processor






				def 		snake_case	(			self      ,*snake_case__      ,**snake_case__ ):
							return self.tokenizer.batch_decode(*snake_case__      ,**snake_case__ )






				def 		snake_case	(			self      ,*snake_case__      ,**snake_case__ ):
							return self.tokenizer.decode(*snake_case__      ,**snake_case__ )






				@property
				# Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : List[Any]					  =      self.tokenizer.model_input_names
							SCREAMING_SNAKE_CASE_   : int					  =      self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )











"""simple docstring"""


import itertools
import math


def        UpperCAmelCase      (					a__ ):





						'''simple docstring'''






						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5     ,      int(math.sqrt(a__ ) + 1 )     ,      6 ):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True


def        UpperCAmelCase      (					):





						'''simple docstring'''






						lowerCAmelCase   :str						=			2
						while True:
												if is_prime(a__ ):
																		yield num
												num += 1


def        UpperCAmelCase      (					a__ = 1_00_01 ):





						'''simple docstring'''






						return next(itertools.islice(prime_generator()     ,      nth - 1     ,      a__ ) )


if __name__ == "__main__":
		print(F"""{solution() = }""")